In order to achieve an audio signal with good quality, it is generally necessary to process the audio signal. Such an audio signal processing task involves audio signal analysis and audio signal processing based on the analysis results to calibrate and present the audio signal (such as, playback of the audio signal). Typically the audio signal processing may include equalization processing, volume control, noise elimination, peak limiting processing, and so forth.
Audio processing systems are generally designed depending on factors such as latency, computational complexity, or signal distortion requirements. In conventional audio processing systems, an audio signal analysis and processing procedure comprises transforms between time domain and frequency domain. For example, an input audio signal is generally divided into frames by windowing. The frames are then transformed into the frequency domain so that energy, power, or spectrum characteristics of the audio signal can be analyzed at the frequency subband level. After that analysis, the audio signal transformed in the frequency domain is processed using the analysis results, and then the processed audio signal is transformed back to the time domain for playback. A plurality of filters/filterbanks can be designed for both analysis and processing purposes.
There is a tradeoff between audio processing latency, computational complexity and signal distortion. To achieve a powerful signal analysis, known approaches have to operate with high computational complexity or significant latency. More specifically, longer latency is introduced in the known approaches due to the framing of the audio signal and the use of the filterbanks that the audio signal passes through. Long latency of the audio signal processing is very likely to decrease the overall performance of the systems and has negative impacts on user experience, especially for cases that need real time processing, such as instant voice communications. On the other hand, in order to obtain perfect reconstruction (PR) of the audio signal, the filterbanks used for time-to-frequency transforming and corresponding inverse transforming are subject to additional constraints, which would potentially introduce band isolation and imperfect linear convolution issues. Most filterbank approaches used in the transforms generally process signals in a critically sampled manner (for example, signals in subbands are highly decimated) and such approaches would introduce harmonic distortions during the audio signal processing.